Abstract

Edge Computing paradigms are expected to solve some major problems affecting current application scenarios that rely on Cloud computing resources to operate. These novel paradigms will bring computational resources closer to the users and by doing so they will not only reduce network latency and bandwidth utilization but will also introduce some attractive context-awareness features to these systems. In this paper we show how the enticing features introduced by Edge Computing paradigms can be exploited to improve security and privacy in the critical scenario of vehicular networks (VN), especially existing authentication and revocation issues. In particular, we analyze the security challenges in VN and describe three deployment models for vehicular edge computing, which refrain from using vehicular- to-vehicular communications. The result is that the burden imposed to vehicles is considerably reduced without sacrificing the security or functional features expected in vehicular scenarios.

Abstract

For various reasons, the cloud computing paradigm is unable to meet certain requirements (e.g. low latency and jitter, context awareness, mobility support) that are crucial for several applications (e.g. vehicular networks, augmented reality). To fulfil these requirements, various paradigms, such as fog computing, mobile edge computing, and mobile cloud computing, have emerged in recent years. While these edge paradigms share several features, most of the existing research is compartmentalised; no synergies have been explored. This is especially true in the field of security, where most analyses focus only on one edge paradigm, while ignoring the others. The main goal of this study is to holistically analyse the security threats, challenges, and mechanisms inherent in all edge paradigms, while highlighting potential synergies and venues of collaboration. In our results, we will show that all edge paradigms should consider the advances in other paradigms.

Abstract

Cloud computing has some major limitations that hinder its application to some specific scenarios (e.g., Industrial IoT, and remote surgery) where there are particularly stringent requirements, such as extremely low latency. Fog computing is a specialization of the Cloud that promises to overcome the aforementioned limitations by bringing the Cloud closer to end-users. Despite its potential benefits, Fog Computing is still a developing paradigm which demands further research, especially on security and privacy aspects. This is precisely the focus of this paper: to make evident the urgent need for security mechanisms in Fog computing, as well as to present a research strategy with the necessary steps and processes that are being undertaken within the scope of the SMOG project, in order to enable a trustworthy and resilient Fog ecosystem.

Abstract

This paper analyzes the secure access delegation problem, which occurs naturally in the cloud, and postulate that Proxy Re-Encryption is a feasible cryptographic solution, both from the functional and efficiency perspectives. Proxy re-encryption is a special type of public-key encryption that permits a proxy to transform ciphertexts from one public key to another, without the proxy being able to learn any information about the original message. Thus, it serves as a means for delegating decryption rights, opening up many possible applications that require of delegated access to encrypted data. In particular, sharing information in the cloud is a prime example. In this paper, we review the main proxy re-encryption schemes so far, and provide a detailed analysis of their characteristics. Additionally, we also study the efficiency of selected schemes, both theoretically and empirically, based on our own implementation. Finally, we discuss some applications of proxy re-encryption, with a focus on secure access delegation in the cloud.

Abstract

Transparency and verifiability are necessary aspects of accountability, but care needs to be taken that auditing is done in a privacy friendly way. There are situations where it would be useful for certain actors to be able to make restricted views within service provision chains on accountability evidence, including logs, available to other actors with specific governance roles. For example, a data subject or a Data Protection Authority (DPA) might want to authorize an accountability agent to act on their behalf, and be given access to certain logs in a way that does not compromise the privacy of other actors or the security of involved data processors. In this paper two cryptographic-based techniques that may address this issue are proposed and assessed.

Abstract

In this paper we tackle the problem of privacy and confidentiality in Identity Management as a Service (IDaaS). The adoption of cloud computing technologies by organizations has fostered the externalization of the identity management processes, shaping the concept of Identity Management as a Service. However, as it has happened to other cloud-based services, the cloud poses serious risks to the users, since they lose the control over their data. As part of this work, we analyze these concerns and present a model for privacy-preserving IDaaS, called BlindIdM, which is designed to provide data privacy protection through the use of cryptographic safeguards.

Abstract

Cloud computing is becoming a key IT infrastructure technology being adopted progressively by companies and users. Still, there are issues and uncertainties surrounding its adoption, such as security and how users data is dealt with that require attention from developers, researchers, providers and users. The A4Cloud project tries to help solving the problem of accountability in the cloud by providing tools that support the process of achieving accountability. This paper presents the contents of the first A4Cloud tutorial. These contents include basic concepts and tools developed within the project. In particular, we will review how metrics can aid the accountability process and some of the tools that the A4Cloud project will produce such as the Data Track Tool (DTT) and the Cloud Offering Advisory Tool (COAT).

Abstract

Identity management is an almost indispensable component of today’s organizations and companies, as it plays a key role in authentication and access control; however, at the same time it is widely recognized as a costly and time-consuming task. The advent of cloud computing technologies, together with the promise of flexible, cheap and efficient provision of services, has provided the opportunity to externalize such a common process, shaping what has been called Identity Management as a Service (IDaaS). Nevertheless, as in the case of other cloud-based services, IDaaS brings with it great concerns regarding security and privacy, such as the loss of control over the outsourced data. In this paper we analyze these concerns and propose BlindIdM, a model for privacy-preserving IDaaS with a focus on data privacy protection. In particular, we describe how a SAML-based system can be augmented to employ proxy re-encryption techniques for achieving data condentiality with respect to the cloud provider, while preserving the ability to supply the identity service. This is an innovative contribution to both the privacy and identity management landscapes.

Abstract

Among Big Data technologies, Hadoop stands out for its capacity to store and process large-scale datasets. However, although Hadoop was not designed with security in mind, it is widely used by plenty of organizations, some of which have strong data protection requirements. Traditional access control solutions are not enough, and cryptographic solutions must be put in place to protect sensitive information. In this paper, we describe a cryptographically-enforced access control system for Hadoop, based on proxy re-encryption. Our proposed solution fits in well with the outsourcing of Big Data processing to the cloud, since information can be stored in encrypted form in external servers in the cloud and processed only if access has been delegated. Experimental results show that the overhead produced by our solution is manageable, which makes it suitable for some applications.

Abstract

Cloud applications entail the provision of a huge amount of heterogeneous, geographically-distributed resources managed and shared by many different stakeholders who often do not know each other beforehand. This raises numerous security concerns that, if not addressed carefully, might hinder the adoption of this promising computational model. Appropriately dealing with these threats gains special relevance in the social cloud context, where computational resources are provided by the users themselves. We argue that taking trust and reputation requirements into account can leverage security in these scenarios by incorporating the notions of trust relationships and reputation into them. For this reason, we propose a development framework onto which developers can implement trust-aware social cloud applications. Developers can also adapt the framework in order to accommodate their application-specific needs.

Abstract

The advent of cloud computing has provided the opportunity to externalize the identity management processes, shaping what has been called Identity Management as a Service (IDaaS). However, as in the case of other cloud-based services, IDaaS brings with it great concerns regarding security and privacy, such as the loss of control over the outsourced data. As part of this PhD thesis, we analyze these concerns and propose BlindIdM, a model for privacy-preserving IDaaS with a focus on data privacy protection through the use of proxy re-encryption.

Abstract

Cloud governance, and in particular data governance in the cloud, relies on different technical and organizational practices and procedures, such as policy enforcement, risk management, incident management and remediation. The concept of accountability encompasses such practices, and is essential for enhancing security and trustworthiness in the cloud. Besides this, proper measurement of cloud services, both at a technical and governance level, is a distinctive aspect of the cloud computing model. Hence, a natural problem that arises is how to measure the impact on accountability of the procedures held in practice by organizations that participate in the cloud ecosystem. In this paper, we describe a metamodel for addressing the problem of measuring accountability properties for cloud computing, as discussed and defined by the Cloud Accountability Project (A4Cloud). The goal of this metamodel is to act as a language for describing: (i) accountability properties in terms of actions between entities, and (ii) metrics for measuring the fulfillment of such properties. It also allows the recursive decomposition of properties and metrics, from a high-level and abstract world to a tangible and measurable one. Finally, we illustrate our proposal of the metamodel by modelling the transparency property, and define some metrics for it.

Abstract

The inclusion of identity management in the cloud computing landscape represents a new business opportunity for providing what has been called Identity Management as a Service (IDaaS). Nevertheless, IDaaS introduces the same kind of problems regarding privacy and data confidentiality as other cloud services; on top of that, the nature of the outsourced information (users’ identity) is critical. Traditionally, cloud services (including IDaaS) rely only on SLAs and security policies to protect the data, but these measures have proven insufficient in some cases; recent research has employed advanced cryptographic mechanisms as an additional safeguard. Apart from this, there are several identity management schemes that could be used for realizing IDaaS systems in the cloud; among them, OpenID has gained crescent popularity because of its open and decentralized nature, which makes it a prime candidate for this task. In this paper we demonstrate how a privacy-preserving IDaaS system can be implemented using OpenID Attribute Exchange and a proxy re-encryption scheme. Our prototype enables an identity provider to serve attributes to other parties without being able to read their values. This proposal constitutes a novel contribution to both privacy and identity management fields. Finally, we discuss the performance and economical viability of our proposal.

Abstract

In this paper we identify some areas where cryptography can help a rapid adoption of cloud computing. Although secure storage has already captured the attention of many cloud providers, offering a higher level of protection for their customer’s data, we think that more advanced techniques such as searchable encryption and secure outsourced computation will become popular in the near future, opening the doors of the Cloud to customers with higher security requirements.

Abstract

Intercloud notion is gaining a lot of attention lately from both enterprise and academia, not only because of its benefits and expected results but also due to the challenges that it introduces regarding interoperability and standardisation. Identity management services are one of the main candidates to be outsourced into the Intercloud, since they are one of the most common services needed by companies and organisations. This paper addresses emerging identity management challenges that arise in intercloud formations, such as naming, identification, interoperability, identity life cycle management and single sign-on.

Abstract

During the last decade, the Cloud Computing paradigm has emerged as a panacea for many problems in traditional IT infrastructures. Much has been said about the potential of Cloud Computing in the Smart Grid context, but unfortunately it is still relegated to a second layer when it comes to critical systems. Although the advantages of outsourcing those kind of applications to the cloud is clear, data confidentiality and operational privacy stand as mayor drawbacks. In this paper, we try to give some hints on which security mechanisms and more specific, which cryptographic schemes, will help a better integration of Smart Grids and Clouds. We propose the use of Virtual SCADA in the Cloud (VS-Cloud) as a mean to improve reliability and efficiency whilst maintaining the same protection level as in traditional SCADA architectures.